Data processing

ABSTRACT

One or more processors acquire dependency metadata, where the dependency metadata is used for representing dependency on data among at least two components of an application. The processor(s) acquire error information and data output, where the error information is used for describing errors that occur while running the application, and where the data output includes data output by the at least two components while running the application. The processor(s) analyze, based on the error information, dependency metadata and data output relevant to the error information, where the analyzing includes determining, based on a null pointer exception in the error information and data output of a component corresponding to the null pointer exception, that there is an error in dependency metadata corresponding to the null pointer exception. The processor(s) then provide an analysis result to improve the operation of a computer that is running the application.

BACKGROUND

The present invention relates to field of information processing, morespecifically, to a data processing method and apparatus.

With continuous development in application development technology, moreand more applications do not employ the approach of integrateddevelopment any longer, rather, they are separated into a plurality ofcomponents for development. There is data dependency and orderconstraints among the plurality of components constituting anapplication.

The plurality of components constituting an application may be developedby different developers, or there may be a component that can be reusedin the plurality of components, that is, there may be a commoncomponent. All these may cause error in data dependency and orderconstraints, thereby making the entire application unable to run.

If an error is reported in running an application, whether for adeveloper or a user of the application, it is hard to determine thereason leading to the error, and a tremendous effort will be needed tocorrect the error. Therefore, there is a need for a simple and easysolution to prompt for a reason leading to an error or prompt for anerror correction method.

SUMMARY

In accordance with one or more embodiments of the present invention, aprocessor-implemented method, computer system, and/or computer programproduct analyzes data processing. One or more processors acquiredependency metadata, where the dependency metadata is used forrepresenting dependency on data among at least two components of anapplication. The processor(s) acquire error information and data output,where the error information is used for describing errors that occurwhile running the application, and where the data output includes dataoutput by the at least two components while running the application. Theprocessor(s) analyze, based on the error information, dependencymetadata and data output relevant to the error information, where theanalyzing includes determining, based on a null pointer exception in theerror information and data output of a component corresponding to thenull pointer exception, that there is an error in dependency metadatacorresponding to the null pointer exception. The processor(s) provide ananalysis result, where the analysis result includes at least one of: areason why an error occurs, a prompt for an error correction method, arelevant dependency metadata leading to an occurrence of an error, andrelevant data output leading to an occurrence of an error. Theprocessor(s) adjust an operation of a computer that is executing theapplication based on the analysis result.

BRIEF DESCRIPTION OF THE DRAWINGS

Through the more detailed description of some embodiments of the presentdisclosure in the accompanying drawings, the above and other objects,features and advantages of the present disclosure will become moreapparent, wherein the same reference generally refers to the samecomponents in the embodiments of the present disclosure.

FIG. 1 depicts a cloud computing node according to an embodiment of thepresent invention.

FIG. 2 depicts a cloud computing environment according to an embodimentof the present invention.

FIG. 3 depicts abstraction model layers according to an embodiment ofthe present invention.

FIG. 4 depicts a flowchart of a data processing method according to anembodiment of the present invention.

FIG. 5 depicts a flowchart of a data processing method according to anembodiment of the present invention.

FIG. 6 depicts a flowchart of an example implemented by a dataprocessing method according to an embodiment of the present invention.

FIG. 7 depicts a structure diagram of a data processing apparatusaccording to an embodiment of the present invention.

DETAILED DESCRIPTION

The present invention may be a system, a method, and/or a computerprogram product. The computer program product may include a computerreadable storage medium (or media) having computer readable programinstructions thereon for causing a processor to carry out aspects of thepresent invention.

The computer readable storage medium can be a tangible device that canretain and store instructions for use by an instruction executiondevice. The computer readable storage medium may be, for example, but isnot limited to, an electronic storage device, a magnetic storage device,an optical storage device, an electromagnetic storage device, asemiconductor storage device, or any suitable combination of theforegoing. A non-exhaustive list of more specific examples of thecomputer readable storage medium includes the following: a portablecomputer diskette, a hard disk, a random access memory (RAM), aread-only memory (ROM), an erasable programmable read-only memory (EPROMor Flash memory), a static random access memory (SRAM), a portablecompact disc read-only memory (CD-ROM), a digital versatile disk (DVD),a memory stick, a floppy disk, a mechanically encoded device such aspunch-cards or raised structures in a groove having instructionsrecorded thereon, and any suitable combination of the foregoing. Acomputer readable storage medium, as used herein, is not to be construedas being transitory signals per se, such as radio waves or other freelypropagating electromagnetic waves, electromagnetic waves propagatingthrough a waveguide or other transmission media (e.g., light pulsespassing through a fiber-optic cable), or electrical signals transmittedthrough a wire.

Computer readable program instructions described herein can bedownloaded to respective computing/processing devices from a computerreadable storage medium or to an external computer or external storagedevice via a network, for example, the Internet, a local area network, awide area network and/or a wireless network. The network may comprisecopper transmission cables, optical transmission fibers, wirelesstransmission, routers, firewalls, switches, gateway computers and/oredge servers. A network adapter card or network interface in eachcomputing/processing device receives computer readable programinstructions from the network and forwards the computer readable programinstructions for storage in a computer readable storage medium withinthe respective computing/processing device.

Computer readable program instructions for carrying out operations ofthe present invention may be assembler instructions,instruction-set-architecture (ISA) instructions, machine instructions,machine dependent instructions, microcode, firmware instructions,state-setting data, or either source code or object code written in anycombination of one or more programming languages, including an objectoriented programming language such as Smalltalk, C++ or the like, andconventional procedural programming languages, such as the “C”programming language or similar programming languages. The computerreadable program instructions may execute entirely on the user'scomputer, partly on the user's computer, as a stand-alone softwarepackage, partly on the user's computer and partly on a remote computeror entirely on the remote computer or server. In the latter scenario,the remote computer may be connected to the user's computer through anytype of network, including a local area network (LAN) or a wide areanetwork (WAN), or the connection may be made to an external computer(for example, through the Internet using an Internet Service Provider).In some embodiments, electronic circuitry including, for example,programmable logic circuitry, field-programmable gate arrays (FPGA), orprogrammable logic arrays (PLA) may execute the computer readableprogram instructions by utilizing state information of the computerreadable program instructions to personalize the electronic circuitry,in order to perform aspects of the present invention.

Aspects of the present invention are described herein with reference toflowchart illustrations and/or block diagrams of methods, apparatus(systems), and computer program products according to embodiments of theinvention. It will be understood that each block of the flowchartillustrations and/or block diagrams, and combinations of blocks in theflowchart illustrations and/or block diagrams, can be implemented bycomputer readable program instructions.

These computer readable program instructions may be provided to aprocessor of a general purpose computer, special purpose computer, orother programmable data processing apparatus to produce a machine, suchthat the instructions, which execute via the processor of the computeror other programmable data processing apparatus, create means forimplementing the functions/acts specified in the flowchart and/or blockdiagram block or blocks. These computer readable program instructionsmay also be stored in a computer readable storage medium that can directa computer, a programmable data processing apparatus, and/or otherdevices to function in a particular manner, such that the computerreadable storage medium having instructions stored therein comprises anarticle of manufacture including instructions which implement aspects ofthe function/act specified in the flowchart and/or block diagram blockor blocks.

The computer readable program instructions may also be loaded onto acomputer, other programmable data processing apparatus, or other deviceto cause a series of operational steps to be performed on the computer,other programmable apparatus or other device to produce a computerimplemented process, such that the instructions which execute on thecomputer, other programmable apparatus, or other device implement thefunctions/acts specified in the flowchart and/or block diagram block orblocks.

The flowchart and block diagrams in the Figures illustrate thearchitecture, functionality, and operation of possible implementationsof systems, methods, and computer program products according to variousembodiments of the present invention. In this regard, each block in theflowchart or block diagrams may represent a module, segment, or portionof instructions, which comprises one or more executable instructions forimplementing the specified logical function(s). In some alternativeimplementations, the functions noted in the block may occur out of theorder noted in the figures. For example, two blocks shown in successionmay, in fact, be executed substantially concurrently, or the blocks maysometimes be executed in the reverse order, depending upon thefunctionality involved. It will also be noted that each block of theblock diagrams and/or flowchart illustration, and combinations of blocksin the block diagrams and/or flowchart illustration, can be implementedby special purpose hardware-based systems that perform the specifiedfunctions or acts or carry out combinations of special purpose hardwareand computer instructions.

Some preferable embodiments will be described in more detail withreference to the accompanying drawings, in which the preferableembodiments of the present disclosure have been illustrated. However,the present disclosure can be implemented in various manners, and thusshould not be construed to be limited to the embodiments disclosedherein. On the contrary, those embodiments are provided for the thoroughand complete understanding of the present disclosure, and completelyconveying the scope of the present disclosure to those skilled in theart.

It is understood in advance that although this disclosure includes adetailed description on cloud computing, implementation of the teachingsrecited herein are not limited to a cloud computing environment. Rather,embodiments of the present invention are capable of being implemented inconjunction with any other type of computing environment now known orlater developed.

Cloud computing is a model of service delivery for enabling convenient,on-demand network access to a shared pool of configurable computingresources (e.g. networks, network bandwidth, servers, processing,memory, storage, applications, virtual machines, and services) that canbe rapidly provisioned and released with minimal management effort orinteraction with a provider of the service. This cloud model may includeat least five characteristics, at least three service models, and atleast four deployment models.

Characteristics are as Follows:

On-demand self-service: a cloud consumer can unilaterally provisioncomputing capabilities, such as server time and network storage, asneeded automatically without requiring human interaction with theservice's provider.

Broad network access: capabilities are available over a network andaccessed through standard mechanisms that promote use by heterogeneousthin or thick client platforms (e.g., mobile phones, laptops, and PDAs).

Resource pooling: the provider's computing resources are pooled to servemultiple consumers using a multi-tenant model, with different physicaland virtual resources dynamically assigned and reassigned according todemand. There is a sense of location independence in that the consumergenerally has no control or knowledge over the exact location of theprovided resources but may be able to specify location at a higher levelof abstraction (e.g., country, state, or datacenter).

Rapid elasticity: capabilities can be rapidly and elasticallyprovisioned, in some cases automatically, to quickly scale out andrapidly released to quickly scale in. To the consumer, the capabilitiesavailable for provisioning often appear to be unlimited and can bepurchased in any quantity at any time.

Measured service: cloud systems automatically control and optimizeresource use by leveraging a metering capability at some level ofabstraction appropriate to the type of service (e.g., storage,processing, bandwidth, and active user accounts). Resource usage can bemonitored, controlled, and reported providing transparency for both theprovider and consumer of the utilized service.

Service Models are as follows:

Software as a Service (SaaS): the capability provided to the consumer isto use the provider's applications running on a cloud infrastructure.The applications are accessible from various client devices through athin client interface such as a web browser (e.g., web-based e-mail).The consumer does not manage or control the underlying cloudinfrastructure including network, servers, operating systems, storage,or even individual application capabilities, with the possible exceptionof limited user-specific application configuration settings.

Platform as a Service (PaaS): the capability provided to the consumer isto deploy onto the cloud infrastructure consumer-created or acquiredapplications created using programming languages and tools supported bythe provider. The consumer does not manage or control the underlyingcloud infrastructure including networks, servers, operating systems, orstorage, but has control over the deployed applications and possiblyapplication hosting environment configurations.

Infrastructure as a Service (IaaS): the capability provided to theconsumer is to provision processing, storage, networks, and otherfundamental computing resources where the consumer is able to deploy andrun arbitrary software, which can include operating systems andapplications. The consumer does not manage or control the underlyingcloud infrastructure but has control over operating systems, storage,deployed applications, and possibly limited control of select networkingcomponents (e.g., host firewalls).

Deployment Models are as follows:

Private cloud: the cloud infrastructure is operated solely for anorganization. It may be managed by the organization or a third party andmay exist on-premises or off-premises.

Community cloud: the cloud infrastructure is shared by severalorganizations and supports a specific community that has shared concerns(e.g., mission, security requirements, policy, and complianceconsiderations). It may be managed by the organizations or a third partyand may exist on-premises or off-premises.

Public cloud: the cloud infrastructure is made available to the generalpublic or a large industry group and is owned by an organization sellingcloud services.

Hybrid cloud: the cloud infrastructure is a composition of two or moreclouds (private, community, or public) that remain unique entities butare bound together by standardized or proprietary technology thatenables data and application portability (e.g., cloud bursting forload-balancing between clouds).

A cloud computing environment is service oriented with a focus onstatelessness, low coupling, modularity, and semantic interoperability.At the heart of cloud computing is an infrastructure comprising anetwork of interconnected nodes.

Referring now to FIG. 1, a schematic of an example of a cloud computingnode is shown. Cloud computing node 10 is only one example of a suitablecloud computing node and is not intended to suggest any limitation as tothe scope of use or functionality of embodiments of the inventiondescribed herein. Regardless, cloud computing node 10 is capable ofbeing implemented and/or performing any of the functionality set forthhereinabove.

In cloud computing node 10 there is a computer system/server 12, whichis operational with numerous other general purpose or special purposecomputing system environments or configurations. Examples of well-knowncomputing systems, environments, and/or configurations that may besuitable for use with computer system/server 12 include, but are notlimited to, personal computer systems, server computer systems, thinclients, thick clients, hand-held or laptop devices, multiprocessorsystems, microprocessor-based systems, set top boxes, programmableconsumer electronics, network PCs, minicomputer systems, mainframecomputer systems, and distributed cloud computing environments thatinclude any of the above systems or devices, and the like.

Computer system/server 12 may be described in the general context ofcomputer system-executable instructions, such as program modules, beingexecuted by a computer system. Generally, program modules may includeroutines, programs, objects, components, logic, data structures, and soon that perform particular tasks or implement particular abstract datatypes. Computer system/server 12 may be practiced in distributed cloudcomputing environments where tasks are performed by remote processingdevices that are linked through a communications network. In adistributed cloud computing environment, program modules may be locatedin both local and remote computer system storage media including memorystorage devices.

As shown in FIG. 1, computer system/server 12 in cloud computing node 10is shown in the form of a general-purpose computing device. Thecomponents of computer system/server 12 may include, but are not limitedto, one or more processors or processing units 16, a system memory 28,and a bus 18 that couples various system components including systemmemory 28 to processor 16.

Bus 18 represents one or more of any of several types of bus structures,including a memory bus or memory controller, a peripheral bus, anaccelerated graphics port, and a processor or local bus using any of avariety of bus architectures. By way of example, and not limitation,such architectures include Industry Standard Architecture (ISA) bus,Micro Channel Architecture (MCA) bus, Enhanced ISA (EISA) bus, VideoElectronics Standards Association (VESA) local bus, and PeripheralComponent Interconnect (PCI) bus.

Computer system/server 12 typically includes a variety of computersystem readable media. Such media may be any available media that isaccessible by computer system/server 12, and it includes both volatileand non-volatile media, removable and non-removable media.

System memory 28 can include computer system readable media in the formof volatile memory, such as random access memory (RAM) 30 and/or cachememory 32. Computer system/server 12 may further include otherremovable/non-removable, volatile/non-volatile computer system storagemedia. By way of example only, storage system 34 can be provided forreading from and writing to a non-removable, non-volatile magnetic media(not shown and typically called a “hard drive”). Although not shown, amagnetic disk drive for reading from and writing to a removable,non-volatile magnetic disk (e.g., a “floppy disk”), and an optical diskdrive for reading from or writing to a removable, non-volatile opticaldisk such as a CD-ROM, DVD-ROM or other optical media can be provided.In such instances, each can be connected to bus 18 by one or more datamedia interfaces. As will be further depicted and described below,memory 28 may include at least one program product having a set (e.g.,at least one) of program modules that are configured to carry out thefunctions of embodiments of the invention.

Program/utility 40, having a set (at least one) of program modules 42,may be stored in memory 28 by way of example, and not limitation, aswell as an operating system, one or more application programs, otherprogram modules, and program data. Each of the operating system, one ormore application programs, other program modules, and program data orsome combination thereof, may include an implementation of a networkingenvironment. Program modules 42 generally carry out the functions and/ormethodologies of embodiments of the invention as described herein.

Computer system/server 12 may also communicate with one or more externaldevices 14 such as a keyboard, a pointing device, a display 24, etc.;one or more devices that enable a user to interact with computersystem/server 12; and/or any devices (e.g., network card, modem, etc.)that enable computer system/server 12 to communicate with one or moreother computing devices. Such communication can occur via Input/Output(I/O) interfaces 22. Still yet, computer system/server 12 cancommunicate with one or more networks such as a local area network(LAN), a general wide area network (WAN), and/or a public network (e.g.,the Internet) via network adapter 20. As depicted, network adapter 20communicates with the other components of computer system/server 12 viabus 18. It should be understood that although not shown, other hardwareand/or software components could be used in conjunction with computersystem/server 12. Examples, include, but are not limited to: microcode,device drivers, redundant processing units, external disk drive arrays,RAID systems, tape drives, and data archival storage systems, etc.

Referring now to FIG. 2, illustrative cloud computing environment 50 isdepicted. As shown, cloud computing environment 50 comprises one or morecloud computing nodes 10 with which local computing devices used bycloud consumers, such as, for example, personal digital assistant (PDA)or cellular telephone 54A, desktop computer 54B, laptop computer 54C,and/or automobile computer system 54N may communicate. Nodes 10 maycommunicate with one another. They may be grouped (not shown) physicallyor virtually, in one or more networks, such as Private, Community,Public, or Hybrid clouds as described hereinabove, or a combinationthereof. This allows cloud computing environment 50 to offerinfrastructure, platforms and/or software as services for which a cloudconsumer does not need to maintain resources on a local computingdevice. It is understood that the types of computing devices 54A-N shownin FIG. 2 are intended to be illustrative only and that computing nodes10 and cloud computing environment 50 can communicate with any type ofcomputerized device over any type of network and/or network addressableconnection (e.g., using a web browser).

Referring now to FIG. 3, a set of functional abstraction layers providedby cloud computing environment 50 (FIG. 2) is shown. It should beunderstood in advance that the components, layers, and functions shownin FIG. 3 are intended to be illustrative only and embodiments of theinvention are not limited thereto. As depicted, the following layers andcorresponding functions are provided:

Hardware and software layer 60 includes hardware and softwarecomponents. Examples of hardware components include mainframes, in oneexample IBM® zSeries® systems; RISC (Reduced Instruction Set Computer)architecture based servers, in one example IBM pSeries® systems; IBMxSeries® systems; IBM BladeCenter® systems; storage devices; networksand networking components. Examples of software components includenetwork application server software, in one example IBM Web Sphere®application server software; and database software, in one example IBMDB2® database software. (IBM, zSeries, pSeries, xSeries, BladeCenter,WebSphere, and DB2 are trademarks of International Business MachinesCorporation registered in many jurisdictions worldwide).

Virtualization layer 62 provides an abstraction layer from which thefollowing examples of virtual entities may be provided: virtual servers;virtual storage; virtual networks, including virtual private networks;virtual applications and operating systems; and virtual clients.

In one example, management layer 64 may provide the functions describedbelow. Resource provisioning provides dynamic procurement of computingresources and other resources that are utilized to perform tasks withinthe cloud computing environment. Metering and Pricing provide costtracking as resources are utilized within the cloud computingenvironment, and billing or invoicing for consumption of theseresources. In one example, these resources may comprise applicationsoftware licenses. Security provides identity verification for cloudconsumers and tasks, as well as protection for data and other resources.User portal provides access to the cloud computing environment forconsumers and system administrators. Service level management providescloud computing resource allocation and management such that requiredservice levels are met. Service Level Agreement (SLA) planning andfulfillment provide pre-arrangement for, and procurement of, cloudcomputing resources for which a future requirement is anticipated inaccordance with an SLA.

Workloads layer 66 provides examples of functionality for which thecloud computing environment may be utilized. Examples of workloads andfunctions which may be provided from this layer include: mapping andnavigation; software development and lifecycle management; virtualclassroom education delivery; data analytics processing; transactionprocessing.

With reference now to FIG. 4, an embodiment of the invention provides adata processing method. The method comprises: step 410, acquiringdependency metadata; step 430, acquiring error information and dataoutput; step 450, analyzing, based on the error information, dependencymetadata and data output relevant to that error information; step 470,providing analysis result. In the present embodiment, the dependencymetadata is used for representing dependency on data among at least twocomponents; the error information is used for describing errors thatoccur in running an application including the at least two components,the data output includes data output by components in running theapplication; the analysis result includes at least one of: a reason whyan error occurs, a prompt for an error correction method, a relevantdependency metadata leading to occurrence of an error and relevant dataoutput leading to occurrence of an error. Those skilled in the art canappreciate that data output may include, for example, at least one of aname of output attribute and a value of that attribute. The presentembodiment is applicable to an application including a plurality ofcomponents, wherein the application may be comprised of the plurality ofcomponents or may also include other parts. The application may be aservice, a middleware or an application having specific functions etc.,and the invention has no limitation thereto. By using the technicalsolution provided in the present embodiment, supplemental informationcapable of helping a user to correct errors can be provided based onerror information, data output and dependency metadata. For example, therecorded error information includes: an attribute of component B withname (or id, names in the following embodiments may all be referred toas id) xx1 has read but does not get any data, i.e., null pointerexception. According to dependency metadata, the source of xx1 should bean attribute of component A with name yy1. Based on the recorded dataoutput of component A, it is found that the attribute with name yy1 hasno output. At this point, a reason why an error occurs can be providedto user: because the attribute of component A with name yy1 has nooutput, this leads to the attribute of component B with name xx1 beingunable to acquire the required input. In this way, the user can easilyacquire the reason why an error occurs, so as to conduct correction oncomponent B. Moreover, by utilizing the method provided in the presentembodiment, errors that could not be found in a design can also befound. Still taking the above illustration for example, if an attributeof component A with name yy1 will have output only when it is running,then this error is undiscoverable in the design phase or in anon-operational state, so that this error cannot be corrected. However,by recording error information and data output generated while runningthe application, the solution provided in the present embodiment notonly can find errors that already existed in the design phase, but alsocan find errors that are only presented in the running state, therebyhelping the user to correct various existing errors.

In an embodiment of the invention, the error information includes, forexample, null pointer exception that occurred in reading data.

In an embodiment of the invention, step 450 comprises, for example, atleast one of: determining, based on a null pointer exception in theerror information and dependency metadata corresponding to that nullpointer exception, that corresponding data has not been output by acomponent corresponding to that null pointer exception; determining,based on a null pointer exception in the error information and dataoutput of a component corresponding to that null pointer exception, thatthere is an error in dependency metadata corresponding to that nullpointer exception; determining, based on a null pointer exception in theerror information and data output of a component corresponding to thatnull pointer exception, correct dependency metadata corresponding tothat null pointer exception. Wherein, the step of determining, based ona null pointer exception in the error information and data output of acomponent corresponding to that null pointer exception, correctdependency metadata corresponding to that null pointer exception may forexample repair erroneous dependency metadata, and automatically modifythe erroneous dependency metadata as correct dependency metadata.

Referring to FIG. 5, in an embodiment of the invention, there isprovided a data processing method. The method comprises: step 510,acquiring order constraints; step 530, acquiring data input; step 550,determining redundant order constraints existing in the orderconstraints based on the order constraints and the data input. In thepresent embodiment, the order constraints are used for representingexecution order of the at least two components; the data input includesdata read by components in running the application. Wherein, the datainput includes, in particular, data output by other components and readby components in running the application. Those skilled in the art canappreciate that, the read data may include, for example, at least one ofname of an attribute of data that needs to be read and a value read bythat attribute. With the technical solution provided by the embodiment,existing redundant order constraints may be determined to help the userto adjust or delete order constraints. For example, user has set anorder constraint between components C and D, specifically, component Dneeds to be executed after component C is executed. Through a record ofdata input in running state in the present embodiment, it is found thatcomponent D does not have any data input that is data output of readingcomponent C, thus it can be determined that this order constraint is aredundant order constraint. In this way, the user may delete or adjustredundant order constraints. In another embodiment, the method shown inFIG. 5 may further comprise a step of prompting for the user, i.e.,prompting the redundant order constraint for the user. Further, the usermay be provided with different prompts based on whether redundant orderconstraints are defined in dependency metadata or defined by a user whenbuilding an application.

The embodiment shown in FIG. 4 may be combined with the embodiment shownin FIG. 5. In a combined example, there is no specific order among steps410-470 and steps 510-550.

In another combined example, data input obtained in step 530 may beachieved at the same time as data output obtained in step 430, that is,error information and data input and data output of components arerecorded while running the application. In still another combinedexample, the step of prompting redundant order constraints to the userin the embodiment shown in FIG. 5 may be realized at the same time asstep 470, that is, error information and redundant order constraints areprompted to the user at the same time.

In an embodiment of the invention, step 510 may comprise: acquiringorder constraints by analyzing the acquired dependency metadata, forexample. The embodiment shown in FIG. 5 may further comprise: promptingto the user existing redundant order constraints and dependency metadataleading to the redundant order constraints. Since the redundant orderconstraints are defined in dependency metadata, by prompting redundantorder constraints and relevant dependency metadata to the user, it mayhelp the user to adjust or delete the redundant order constraints.

In an embodiment of the invention, step 510 may comprise: acquiringorder constraints by parsing a profile of an application instance, forexample. Specifically, step 510 may comprise: acquiring the profile ofan application instance from a cloud platform; acquiring orderconstraints by parsing the profile, for example. When building anapplication, the user may define order constraints among a plurality ofcomponents which are contained in a profile of an application instance.Thus, order constraints may be obtained by parsing an applicationinstance obtained from a cloud platform. Those skilled in the art canappreciate that, by combining with other embodiments, the step ofacquiring the profile of an application instance from a cloud platformcan be accomplished in other steps, such as, the step of acquiring theprofile of an application instance from a cloud platform is performed inthe step of acquiring dependency metadata, in this way, step 510 onlyneeds to parse the acquired profile of the application instance toacquire order constraints.

As mentioned above, the invention can either be applied to a cloudcomputing environment or to other computing environment. Next,description will be made by first taking application of an embodiment ina cloud computing environment for example.

In an embodiment of the invention, step 430 comprises: acquiring from acloud platform error information and data output recorded by the cloudplatform, for example. In the embodiment, the error information is usedfor describing errors that occurred in running the application on thecloud platform, the data output includes data output by components inrunning the application on the cloud platform. By using the technicalsolution of the embodiment, running of an application may be placed atcloud platform side and data output and error information of componentsare recorded by the cloud platform, this can reduce requirement forcomputation capability of terminals. Here, steps such as analyzing,etc., are accomplished by terminals, which can reduce workload of thecloud platform and improve performance thereof.

In an embodiment of the invention, step 530 comprises: acquiring from acloud platform data input recorded by the cloud platform, for example.Wherein, the data input includes data read by components in running theapplication on the cloud platform. Those skilled in the art canappreciate that, if both steps 530 and 430 are included in animplementation, these two steps may be accomplished together, that is,error information, data output and data input are acquiredsimultaneously. Accordingly, a cloud platform may also record the errorinformation, data input and data output simultaneously in running anapplication.

In an embodiment of the invention, step 410 comprises: acquiring aprofile of an application instance from a cloud platform; searching alocal environment based on the profile to obtain at least part of thedependency metadata, for example. Still further, a profile of anapplication instance may be acquired by logging into a cloud platform,so as to control acquiring of the application instance by differentusers, and to facilitate a user to build and find his/her ownapplication instances. By using the method provided in the embodiment,local environment may be searched first to obtain dependency metadata,which can reduce communication between terminals and the cloud platformand reduce transmission pressure on network. In another embodiment ofthe invention, the dependency metadata is acquired from the cloudplatform if the dependency metadata could not be found in localenvironment. In specific implementation, required dependency metadatamay be acquired by invoking an API of the cloud platform.

Those skilled in the art can appreciate that, when embodiments of theinvention are implemented in a cloud computing environment, running anapplication in a cloud platform may be achieved by deploying theapplication in a virtual machine.

Next, application of an embodiment of the invention in cloud computingenvironment will be described by taking the illustration shown in FIG. 6for example.

In step 610, logging into a cloud platform to acquire a profile of anapplication instance A. The application instance A includes 4components, that is, component W, component X, component Y and componentZ.

In step 620, parsing the profile of the application instance A toacquire order constraints. By parsing the profile of the applicationinstance A, user defined order constraints are acquired, that is,component Z will be executed after component Y has been executed.

In step 630, searching dependency metadata in a local environment basedon the profile of the application instance A.

In step 640, invoking an API of the cloud platform to acquire dependencymetadata in response to no dependency metadata being found in the localenvironment. Wherein, following dependency metadata is acquired:

{   “source” : “W” ,   “target” : “X” ,   “attributeMapping” : [     {      “sourceid” : “host”,       “targetid” : “dmgrhost”     } ,     {      “sourceid” : “port” ,       “targetid” : “dmgrport”     }   ] } {“source” : “W” , “target” : “Y” , “attributeMapping” : [       {        “sourceid” : “dbctx” ,         “targetid” : “dbctx”       }    ]   } { “source” : “Y” , “target” : “Z” , “attributeMapping” : [      {         “sourceid” : “jmxport” ,         “targetid” : “jmxport”      }     ]   }

In step 650, running the application instance A and recording errorinformation, data output and data input by the cloud platform. Referringto table 1, which is the recorded error information, data input and dataoutput.

TABLE 1 Recorded table of error information, data input and data outputSource Target W.host cell.cc.c X.host cell.cc.c W. mgmtport 8879X.dmgrport null pointer exception W.dbctx No export Y.dbctx null pointerexception Y.jmxport 8800 Z.jmxport no data reading

In step 660, acquiring the error information, data output and data inputfrom the cloud platform. Terminals need to acquire correspondinginformation from the cloud platform.

In step 670, analyzing, based on the error information, dependencymetadata, data output and data input relevant to the error information.In this example, with respect to null pointer exception of X.dmgrportand dependency metadata “sourceid”: “port”, “targetid”: “dmgrport” ofcomponent W and component X, it may be determined that component W doesnot have an attribute with name ‘port’ that has data output, thusX.dmgrport has not read the required data. That is, the dependencymetadata is determined to be erroneous. Further, there is an attributewith name ‘mgmtport’ in component W, which has data output 8879 and thatdata output has not been read, it can thus be determined that correctdependency metadata are “sourceid”: “mgmtport”, “targetid”: “dmgrport”.In this example, with respect to null pointer exception of Y.dbctx anddependency metadata “sourceid”: “dbctx”, “targetid”: “dbctx” ofcomponent W and component Y, it can be determined that dbctx ofcomponent W has no data output. In this example, component Z has notread data output of component Y, it can thus be determined thatcomponent Z does not have to be executed after component Y has beenexecuted.

In step 680, providing an analysis result and prompting redundant orderconstraints. In this example, the analysis result may include a reasonwhy an error occurs, such as “component W has no output with name‘port’, thus ‘dmgrport’ in component X can not read the required data”.In this example, the analysis result may include a prompt for an errorcorrection method, such as “dependency metadata should be modified assourceid:mgmtport, targetid:dmgrport”. Those skilled in the art canappreciate that, according to this example, if there are two attributesin component W which have data output but the data output has not beenread and there are also two attributes in component X which have notread the required data, then the analysis result may include relevantdata output leading to occurrence of an error and/or relevant dependencymetadata leading to occurrence of an error, for example, to prompt aname of an attribute from which component X has not read the requireddata and prompt that there is no data output that has been read in dataoutput of component W, and also to prompt erroneous dependency metadata.In this example, an order constraint may be acquired by analyzingdependency metadata, i.e. “component Z will be executed after componentY has been executed”. It can be found in the above steps that, componentZ does not need to be executed after component Y has been executed, thusin step 680, this redundant order constraint may be prompted to theuser.

Those skilled in the art can appreciate that, in a cloud computingenvironment, embodiments of the invention may also be implemented solelyon a terminal or on a cloud platform. In an embodiment of the invention,step 430 may comprise: running the application and recording errorinformation for describing errors that occur in running the applicationand data output by components in running the application, for example.In an embodiment of the invention, step 530 comprises: running theapplication and recording data read by components in running theapplication, for example.

Moreover, embodiments of the invention may be implemented in a non-cloudcomputing environment. Referring to the above description, embodimentsof the invention may be implemented on two devices that interact witheach other or solely implemented on a single device.

Several probable combinations have been described above through specificexamples, those skilled in the art can appreciate that, more embodimentsmay be obtained through combinations, which will be omitted here forbrevity.

Various embodiments for realizing the method of the invention have beendescribed hereinabove with reference to figures. Those skilled in theart can appreciate that, the above method may be realized in software orhardware, or by a combination thereof. Moreover, those skilled in theart can appreciate that, a data processing apparatus may be provided byimplementing steps in the above method in software, hardware or acombination thereof. Although the apparatus is identical to a generalpurpose processing device in hardware structure, due to functions ofsoftware contained therein, the apparatus is made to present featuresdifferent from a general purpose processing device, thereby forming anapparatus of various embodiments of the invention. A data processingapparatus according to various embodiments of the invention will bedescribed below with reference to FIG. 7.

Referring to FIG. 7, a data processing apparatus 700 provided in anembodiment of the invention is shown. The apparatus may be deployed on aterminal, for example. Preferably, the terminal may communicate with acloud platform and acquire information from the cloud platform. Theapparatus may also be deployed on a cloud platform. The apparatus 700comprises: a relationship acquiring module 710 configured to acquiredependency metadata, wherein the dependency metadata is used forrepresenting dependency on data among at least two components; a firstinformation acquiring module 720 configured to acquire error informationand data output, wherein the error information is used for describingerrors that occur in running an application, the data output includesdata output by components in running the application, the applicationincludes the at least two components; an analyzing module 730 configuredto analyze, based on the error information, dependency metadata and dataoutput relevant to that error information; and a result module 740configured to provide analysis result including at least one of: areason why an error occurs, a prompt for an error correction method,relevant dependency metadata leading to occurrence of an error andrelevant data output leading to an occurrence of an error. With theapparatus provided in this embodiment, supplemental information capableof helping a user to correct errors can be provided based on errorinformation, data output and dependency metadata. This can avoid hugeman power consumption required to find an error by the user manually,and can also help the user to locate an error and reason why the erroroccurs in a faster and more accurate way.

In an embodiment of the invention, the apparatus 700 further comprises:an order acquiring module 750 configured to acquire order constraints,wherein the order constraints are used for representing an executionorder of the at least two components; a second information acquiringmodule 760 configured to acquire data input, wherein the data inputincludes data read by components in running the application; and aredundancy determining module 770 configured to determine redundantorder constraints that exist in the order constraints based on the orderconstraints and the data input. Those skilled in the art can appreciatethat, when this embodiment is implemented by hardware or software, thesecond information acquiring module 760 and the first informationacquiring module 720 may be implemented by a same hardware or softwarecomponent.

In an embodiment of the invention, the order acquiring module 750comprises at least one of the following sub-modules (not shown): a firstorder sub-module configured to acquire order constraints by analyzingthe acquired dependency metadata; a second order sub-module configuredto acquire order constraints by parsing a profile of an applicationinstance. In another embodiment of the invention, the apparatus 700further comprises: a prompting module 780 configured to prompt to theuser existing redundant order constraints and dependency metadataleading to the redundant order constraints.

In an embodiment of the invention, the first information acquiringmodule 720 comprises at least one of: a cloud platform acquiring asub-module configured to acquire from a cloud platform error informationand data output recorded by the cloud platform, wherein the errorinformation is used for describing errors that occur while running theapplication on the cloud platform, the data output includes data outputby components in running the application on the cloud platform; a firstrunning and recording sub-module configured to run the application andrecord error information for describing errors that occur while runningthe application and data output by components in running theapplication. In another embodiment of the invention, if the apparatus isdeployed on a cloud platform, then the first information acquiringmodule 720 comprises the first running and recording sub-module.

In an embodiment of the invention, the relationship acquiring module 710comprises: a profile acquiring sub-module configured to acquire aprofile of an application instance from a cloud platform; a searchingsub-module configured to search a local environment based on the profileto obtain at least part of the dependency metadata. In anotherembodiment of the invention, the relationship acquiring module 710further comprises: a dependency metadata acquiring sub-module configuredto acquire the dependency metadata from the cloud platform if thedependency metadata could not be found in the local environment.

In an embodiment of the invention, the analyzing module 730 comprises atleast one of: a first determining sub-module configured to determine,based on a null pointer exception in the error information anddependency metadata corresponding to that null pointer exception, thatcorresponding data has not been output by a component corresponding tothat null pointer exception; a second determining sub-module configuredto determine, based on a null pointer exception in the error informationand data output of a component corresponding to that null pointerexception, that there is an error in dependency metadata correspondingto that null pointer exception; a third determining sub-moduleconfigured to determine, based on a null pointer exception in the errorinformation and data output of a component corresponding to that nullpointer exception, correct dependency metadata corresponding to thatnull pointer exception.

In an embodiment of the invention, the second information acquiringmodule comprises at least one of: a data input acquiring sub-moduleconfigured to acquire from a cloud platform data input recorded by thecloud platform, wherein the data input includes data read by componentsin running the application on the cloud platform; a second running andrecording sub-module configured to run the application and record dataread by components in running the application.

For implementation details of the above apparatus embodiments, referencemay be made to corresponding method embodiments. Moreover, the aboveapparatus embodiments may be referred to or combined with each other toobtain more implementations, and for detailed combination manner,reference may also be made to the method embodiments and combinationhint given therein.

The present invention relates to field of information processing anddiscloses a data processing method comprising: acquiring dependencymetadata, wherein the dependency metadata is used for representingdependency on data among at least two components; acquiring errorinformation and data output, wherein the error information is used fordescribing errors that occur while running an application, the dataoutput includes data output by components in running the application,the application includes the at least two components; analyzing, basedon the error information, dependency metadata and data output relevantto that error information; providing analysis result including at leastone of: a reason why an error occurs, a prompt for an error correctionmethod, relevant dependency metadata leading to an occurrence of anerror and relevant data output leading to an occurrence of an error.Accordingly, the invention also provides a data processing apparatus.The solution provided in the invention can help user to locate error ina fast and accurate way and correct the error.

In view of the above problems in the art, embodiments of the inventionprovide a data processing method and apparatus to provide a technicalsolution to help to correct errors occurred in an application comprisedof a plurality of components.

According to one aspect of the present invention, there is provided adata processing method, comprising: acquiring dependency metadata,wherein the dependency metadata is used for representing dependency ondata among at least two components; acquiring error information and dataoutput, wherein the error information is used for describing errors thatoccur while running an application, the data output includes data outputby components in running the application, the application includes theat least two components; analyzing, based on the error information,dependency metadata and data output relevant to that error information;providing analysis result including at least one of: a reason why anerror occurs, a prompt for an error correction method, relevantdependency metadata leading to an occurrence of an error and relevantdata output leading to an occurrence of an error.

According to another aspect of the present invention, there is provideda data processing apparatus, comprising: a relationship acquiring moduleconfigured to acquire dependency metadata, wherein the dependencymetadata is used for representing dependency on data among at least twocomponents; a first information acquiring module configured to acquireerror information and data output, wherein the error information is usedfor describing errors that occur while running an application, the dataoutput includes data output by components in running the application,the application includes the at least two components; an analyzingmodule configured to analyze, based on the error information, dependencymetadata and data output relevant to that error information; a resultmodule configured to provide analysis result including at least one of:a reason why an error occurs, a prompt for an error correction method,relevant dependency metadata leading to an occurrence of an error andrelevant data output leading to an occurrence of an error.

The technical solution provided by the invention can help to correcterrors occurred in an application.

The descriptions of the various embodiments of the present inventionhave been presented for purposes of illustration, but are not intendedto be exhaustive or limited to the embodiments disclosed. Manymodifications and variations will be apparent to those of ordinary skillin the art without departing from the scope and spirit of the describedembodiments. The terminology used herein was chosen to best explain theprinciples of the embodiments, the practical application or technicalimprovement over technologies found in the marketplace, or to enableothers of ordinary skill in the art to understand the embodimentsdisclosed herein.

What is claimed is:
 1. A processor-implemented method for analyzing dataprocessing, the processor-implemented method comprising: acquiring, byone or more processors, dependency metadata, wherein the dependencymetadata is used for representing dependency on data among at least twocomponents of an application; acquiring, by one or more processors,error information and data output, wherein the error information is usedfor describing errors that occur while running the application, andwherein the data output includes data output by said at least twocomponents while running the application; analyzing, by one or moreprocessors and based on the error information, dependency metadata anddata output relevant to the error information, wherein said analyzingcomprises determining, based on a null pointer exception in the errorinformation and data output of a component corresponding to the nullpointer exception, that there is an error in dependency metadatacorresponding to the null pointer exception; providing, by one or moreprocessors, an analysis result, wherein the analysis result includes atleast one of: a reason why an error occurs, a prompt for an errorcorrection method, a relevant dependency metadata leading to anoccurrence of an error, and relevant data output leading to anoccurrence of an error; and adjusting, by one or more processors, anoperation of a computer that is executing the application based on theanalysis result.
 2. The processor-implemented method of claim 1, furthercomprising: acquiring, by one or more processors, order constraints,wherein the order constraints are used for representing execution orderof the at least two components; acquiring, by one or more processors,data input, wherein the data input includes data read by components inrunning the application; and determining, by one or more processors,redundant order constraints that exist in the order constraints based onthe order constraints and the data input.
 3. The processor-implementedmethod of claim 2, wherein said acquiring order constraints comprises:acquiring, by one or more processors, order constraints by analyzing theacquired dependency metadata.
 4. The processor-implemented method ofclaim 2, wherein said acquiring order constraints comprises: acquiring,by one or more processors, order constraints by parsing a profile of anapplication instance.
 5. The processor-implemented method of claim 2,further comprising: prompting, by one or more processors and to a user,existing redundant order constraints and dependency metadata leading tothe redundant order constraints.
 6. The processor-implemented method ofclaim 2, wherein said acquiring data input comprises: acquiring, by oneor more processors and from a cloud platform, data input recorded by thecloud platform, wherein the data input includes data read by componentswhile running the application on the cloud platform; and running, by oneor more processors, the application and recording data read bycomponents while running the application.
 7. The processor-implementedmethod of claim 1, wherein said acquiring error information and dataoutput comprises: acquiring, by one or more processors and from a cloudplatform, error information and data output recorded by the cloudplatform, wherein the error information describes errors that occurredwhile running the application on the cloud platform, and wherein thedata output includes data output by components while running theapplication on the cloud platform; re-running, by one or moreprocessors, the application; recording, by one or more processors, errorinformation that describes errors that occurred while running theapplication; and recording, by one or more processors, data output frompredetermined components that occur from running the application.
 8. Acomputer program product comprising one or more computer readablestorage mediums, and program instructions stored on at least one of theone or more storage mediums, the stored program instructions comprising:program instructions to acquire dependency metadata, wherein thedependency metadata is used for representing dependency on data among atleast two components of an application; program instructions to acquireerror information and data output, wherein the error information is usedfor describing errors that occur while running the application, andwherein the data output includes data output by said at least twocomponents while running the application; program instructions toanalyze, based on the error information, dependency metadata and dataoutput relevant to the error information, wherein said the programinstructions to analyze comprise program instructions to determine,based on a null pointer exception in the error information and dataoutput of a component corresponding to the null pointer exception, thatthere is an error in dependency metadata corresponding to the nullpointer exception; program instructions to provide an analysis result,wherein the analysis result includes at least one of: a reason why anerror occurs, a prompt for an error correction method, a relevantdependency metadata leading to an occurrence of an error, and relevantdata output leading to an occurrence of an error; and programinstructions to adjust an operation of a computer that is executing theapplication based on the analysis result.
 9. The computer programproduct of claim 8, further comprising: program instructions to acquireorder constraints, wherein the order constraints are used forrepresenting execution order of the at least two components; programinstructions to acquire data input, wherein the data input includes dataread by components in running the application; and program instructionsto determine redundant order constraints that exist in the orderconstraints based on the order constraints and the data input.
 10. Thecomputer program product of claim 9, wherein the program instructions toacquire order constraints comprise: program instructions to acquireorder constraints by analyzing the acquired dependency metadata.
 11. Thecomputer program product of claim 9, wherein the program instructions toacquire order constraints comprise: program instructions to acquireorder constraints by parsing a profile of an application instance. 12.The computer program product of claim 9, further comprising: programinstructions to prompt, to a user, existing redundant order constraintsand dependency metadata leading to the redundant order constraints. 13.The computer program product of claim 9, wherein the programinstructions to acquire data input comprise: program instructions toacquire, from a cloud platform data, input recorded by the cloudplatform, wherein the data input includes data read by components whilerunning the application on the cloud platform; and program instructionsto run the application and record data read by components while runningthe application.
 14. The computer program product of claim 8, whereinthe program instructions to acquire error information and data outputcomprise: program instructions to acquire, from a cloud platform, errorinformation and data output recorded by the cloud platform, wherein theerror information describes errors that occurred while running theapplication on the cloud platform, and wherein the data output includesdata output by components while running the application on the cloudplatform; program instructions to re-run the application; programinstructions to record error information that describes errors thatoccurred while running the application; and program instructions torecord data output from predetermined components that occur from runningthe application.
 15. A computer system comprising one or moreprocessors, one or more computer readable memories, and one or morecomputer readable storage mediums, and program instructions stored on atleast one of the one or more storage mediums for execution by at leastone of the one or more processors via at least one of the one or morememories, the stored program instructions comprising: programinstructions to acquire dependency metadata, wherein the dependencymetadata is used for representing dependency on data among at least twocomponents of an application; program instructions to acquire errorinformation and data output, wherein the error information is used fordescribing errors that occur while running the application, and whereinthe data output includes data output by said at least two componentswhile running the application; program instructions to analyze, based onthe error information, dependency metadata and data output relevant tothe error information, wherein said the program instructions to analyzecomprise program instructions to determine, based on a null pointerexception in the error information and data output of a componentcorresponding to the null pointer exception, that there is an error independency metadata corresponding to the null pointer exception; programinstructions to provide an analysis result, wherein the analysis resultincludes at least one of: a reason why an error occurs, a prompt for anerror correction method, a relevant dependency metadata leading to anoccurrence of an error, and relevant data output leading to anoccurrence of an error; and program instructions to adjust an operationof a computer that is executing the application based on the analysisresult.
 16. The computer system of claim 15, further comprising: programinstructions to acquire order constraints, wherein the order constraintsare used for representing execution order of the at least twocomponents; program instructions to acquire data input, wherein the datainput includes data read by components in running the application; andprogram instructions to determine redundant order constraints that existin the order constraints based on the order constraints and the datainput.
 17. The computer system of claim 16, wherein the programinstructions to acquire order constraints comprise: program instructionsto acquire order constraints by analyzing the acquired dependencymetadata.
 18. The computer system of claim 16, further comprising:program instructions to prompt, to a user, existing redundant orderconstraints and dependency metadata leading to the redundant orderconstraints.
 19. The computer system of claim 16, wherein the programinstructions to acquire data input comprise: program instructions toacquire, from a cloud platform data, input recorded by the cloudplatform, wherein the data input includes data read by components whilerunning the application on the cloud platform; and program instructionsto run the application and record data read by components while runningthe application.
 20. The computer system of claim 15, wherein theprogram instructions to acquire error information and data outputcomprise: program instructions to acquire, from a cloud platform, errorinformation and data output recorded by the cloud platform, wherein theerror information describes errors that occurred while running theapplication on the cloud platform, and wherein the data output includesdata output by components while running the application on the cloudplatform; program instructions to re-run the application; programinstructions to record error information that describes errors thatoccurred while running the application; and program instructions torecord data output from predetermined components that occur from runningthe application.